A chronic pain trial setting is considered in order to gain insight into the handling of missing data due to patient dropout. When analyzing chronic pain data, a landmark analysis at the study endpoint is considered clinically more relevant than an area-under-the-pain-curve (AUC)-type analysis. Methods that do not assign good scores to missing values due to bad outcome should be used when imputation for missing data is intended. Alternative methods with no explicit imputation are introduced with examples - continuous responder analysis and two-part model analysis - and pros and cons of these methods are discussed.